Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Google Machine Learning and Generative AI for Solutions Architects
  • Table Of Contents Toc
Google Machine Learning and Generative AI for Solutions Architects

Google Machine Learning and Generative AI for Solutions Architects

By : Kieran Kavanagh
4.9 (7)
close
close
Google Machine Learning and Generative AI for Solutions Architects

Google Machine Learning and Generative AI for Solutions Architects

4.9 (7)
By: Kieran Kavanagh

Overview of this book

Most companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies. You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process. By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.
Table of Contents (24 chapters)
close
close
Lock Free Chapter
1
Part 1:The Basics
5
Part 2:Diving in and building AI/ML solutions
17
Part 3:Generative AI

Exploring, visualizing, and preparing data

Use case: We’re planning a trip to New York City, and we want to get an idea of what the best accommodation options would be. Rather than perusing through and evaluating lots of individual Airbnb postings, we’re going to download lots of the reviews and do some bulk data analysis and data processing to get some insights.

We can use the Vertex AI Workbench notebook that we created in Chapter 5 for this purpose. Please open JupyterLab on that notebook instance. In the directory explorer on the left side of the screen, navigate to the Chapter-6 directory and open the Chapter-6-Airbnb.ipynb notebook. You can choose Python (Local) as the kernel. As you did in Chapter 5, run each cell in the notebook by selecting the cell and pressing Shift + Enter on your keyboard.

In the notebook, we use markdown cells to describe each step in detail so that you can understand each step in the process. We use libraries such as pandas, matplotlib...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Google Machine Learning and Generative AI for Solutions Architects
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon